具有时滞的随机神经网络的稳定性  

Exponential Stability of Stochastic Neural Networks with Delay

作　　者：梁莉[1] 吕恕[1] 胡进[1] 杨金祥[1] 

机构地区：[1]电子科技大学应用数学学院,成都610054

出　　处：《电子科技大学学报》2007年第S1期456-458,共3页Journal of University of Electronic Science and Technology of China

摘　　要：研究了具有时滞的随机神经网络模型的稳定性问题,利用Lyapunov函数并结合不等式分析技巧,建立了这种神经网络的均方指数稳定与几乎必然指数稳定的充分条件,其结果推广了细胞神经网络与Hopfield型时滞的随机神经网络的相应结果.In this paper,the exponential stability of stochastic neural networks with delay is investigated.By making use of Lyapunov function and combining with the method of inequality analysis,we establish two types of sufficient conditions for the exponential stability in the mean square and surely exponential stability.The conditions are obtained by extending the results of cellular neural networks and Hopfield stochastic neural networks with delay.

关 键 词：时滞 指数稳定性 神经网络 LYAPUNOV函数 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]